YouTube is the most important online platform for streaming video clips. The popularity and the continuously increasing number of users pose new challenges for Internet Service Providers (ISPs). In particular, in access networks where the transmission resources are limited and the providers are interested in reducing their operational expenditure, it is worth to efficiently optimize the network for popular services such as YouTube. In this paper, we propose different resource management mechanisms to improve the Quality of Experience (QoE) of YouTube users. In particular, we investigate the benefit of cross-layer resource management actions at the client and in the access network for YouTube video streaming. The proposed algorithms are evaluated in a wireless mesh testbed. The results show how to improve the YouTube QoE for the users with the help of client-based or network-based control actions.

Over the last decade, Quality of Experience (QoE) has become a new, central paradigm for understanding the quality of networks and services. In particular, the concept has attracted the interest of communication network and service providers, since being able to guarantee good QoE to customers provides an opportunity for differentiation. In this paper we investigate the potential as well as the implementation challenges of QoE management in the Internet. Using YouTube video streaming service as example, we discuss the different elements that are required for the realization of the paradigm-shift towards truly user-centric network orchestration. To this end, we elaborate QoE management requirements for two complementary network scenarios (wireless mesh Internet access networks vs. global Internet delivery) and provide a QoE model for YouTube taking into account impairments like stalling and initial delay. We present two YouTube QoE monitoring approaches operating on the network and the end user level. Finally, we demonstrate how QoE can be dynamically optimized in both network scenarios with two exemplary concepts, AquareYoum and FoG, respectively. Our results show how QoE management can truly improve the user experience while at the same time increase the efficiency of network resource allocation.

Staehle, B.: Modeling and Optimization Methods for Wireless Sensor and Mesh Networks, received outstanding PhD-theses award 2012 at University of Würzburg, and best dissertation award 2012 of the Institute of Computer Science, (2011).

Internet access networks in general and wireless mesh access networks in particular, are the bottleneck of today’s communication networks and consequently most strongly responsible for determining the user satisfaction. The limited bandwidth and the fact that access network are most often used as mere bit pipes are however unfavorable for the users’ quality of experience (QoE). The lack of application-specific service guarantees is especially inadequate in the face of an increasing degree of heterogeneity of Internet applications and their individual service requirements. Application and quality of experience resource management, Aquarema for short, addresses this challenge by enabling application specific network resource management and thereby improves the user QoE. This is achieved by the interaction of application comfort (AC) monitoring tools, running at the clients, and a network advisor which may trigger different resource management tools. AC quantifies how well an application is running and in particular, enables a prediction of the user experience, thereby allowing the network advisor to act upon an imminent QoE degradation. We demonstrate the appeal of Aquarema at the example of YouTube video streaming in a congested IEEE 802.11 based mesh testbed where AC-aware traffic shaping guarantees the successful video playback.

The paper is devoted to WMN modeling using mixed-integer programming (MIP) formulations that allow to precisely characterize the link data rate capacity and transmission scheduling within time slots. Such MIP models are formulated for several cases of the modulation and coding schemes (MCS) assignment. We present a general way of solving the MMF traffic objective for WMN and use it for the formulated capacity models. Thus the paper combines WMN radio link modeling with a non-standard way of dealing with uncertain traffic, a combination that has not been to our knowledge considered so far in terms of exact optimization models. This combination, involving integer programming, forms the main contribution of the paper. We discuss several ways of solving the considered MMF problems and present an extensive numerical study that illustrates the running time efficiency of the different solution approaches, and the in uence of the MCS selection options and the number of time slots on the traffic performance of a WMN.

The browser has become the users’ interface to a plethora of Internet applications which are accessible from nearly everywhere and every device. The price for the simple and cheap access over the Internet is often a reduced end-user quality of experience (QoE). The reason for this is that the network ignores the content of the packets it transports and thereby neither knows which services it supports, nor if and which quality requirements have to be given. In addition, the needs of the applications can be time varying, and the network might not be able to give strict quality guarantees. We therefore advocate the idea of an application-network interaction in order to dynamically adapt the network resources if a QoE degradation is imminent. The software suite AquareYoum implements this approach and enables a smooth YouTube video playback in a congested wireless mesh Internet access network by dynamically selecting the least congested Internet gateway.

Out of the large number of multimedia content sharing platforms YouTube is the most popular one. This is reflected by the large number of studies which focus on analyzing YouTube characteristics. Techniques for quantifying the instantaneous YouTube QoE and predicting an imminent QoE degradation have in contrast never been proposed. The latter task is even more important if network management actions shall be carried out to avoid a YouTube QoE degradation. In this work we describe YoMo, a tool which constantly monitors the YouTube application comfort. This measure quantifies the application operation condition and allows a QoE prediction. Experiments show that YoMo is able to exactly anticipate an upcoming YouTube QoE degradation.

With an increasing wireless sensor network (WSN) application complexity, more alternatives for the WSN design arose. This complexity is also the reason why it is difficult to asses how and at which price in terms of money or decreased quality of service, design alternatives increase the system performance. In this work we therefore introduce a concept for quickly answering likewise questions, namely the task-based resource consumption modeling. It is the heart of the framework Tuontu which allows to easily estimate if an application is feasible in a given WSN deployment and which performance is to expect.

The problem how to determine the capacity of and achieve fairness in mesh networks is one of the key topics in practical and theoretical research on mesh networks. Max-min fairness is one way to define fairness and several algorithms how to compute max-min fair rate allocations are already published. In this paper we make two major contributions to this area of research: First, we formulate an algorithm achieving max-min fairness among end-to-end flows based on the effective load of a collision domain. This allows us to determine max-min fair rate allocations in a multi-gateway, multi-channel mesh network with equal rates for all links. Second, we extend this algorithm for heterogeneous link rates.

The IEEE 802.11 standard supports a variety of modulation and coding schemes (MCSs). In 802.11-based wireless mesh networks (WMNs) it is hence possible to adapt the link rate to the channel conditions. In particular, smaller link rates may be accepted for an increased spatial reuse. In an earlier study, we showed that this effect is suitable for increasing the max-min fair share throughput in a WMN operating with a TDMA channel access scheme. In this work, we investigate if the use of smaller link rates is also suitable for increasing the throughput of a WMN using a contention-based channel access mechanism. For this purpose, we analytically derive a guideline for link rate assignment as protection against hidden nodes and compute the costs and benefits of this mechanism in terms of MAC layer efficiency. A simulation study shows however that in a medium sized WMN this strategy is less advantageous than assumed and allows to give advices for practical mesh network deployments.

The Internet connection of wireless sensor networks (WSNs) is in general assured by more than one gateway. Planning or optimizing such multi-gateway WSNs (MWSNs) has lately been the focus of the research community. For this purpose, most researchers assume that each sensor node knows about a path to each gateway node. The question how a MWSN can be efficiently started up, i.e. how the sensor nodes learn about the gateways has in contrast not yet been studied thoroughly. To close this gap, we formally describe the problem of starting up a MWSN and demonstrate the importance of optimizing the start-up phase by comparing the performance of an optimal solution to the performance of less efficient distributed algorithms.

In this paper, we introduce a monitoring tool which measures application-specific parameters. These parameters are used to predict the QoE and to perform resource management based on QoE thresholds. We demonstrate the tool for YouTube traffic in an IEEE 802.11 mesh network. Thereby, the QoE is based on the player video buffer size and the resource management can include rerouting, throttling of best effort traffic, or a gateway handover.

During the last years so-called 'Thin Client' architectures have become very popular. Thin Clients are simple end user devices, which are provided with content and services by powerful servers. Originally this concept was developed for Local Area Networks (LANs), which provide a high Quality of Service. If they are used in Wide Area Networks (WANs) they need to be adjusted accordingly in order to guarantee a good Quality of Experience (QoE). In this paper we investigate possibilities for configuring Citrix based Thin Client architectures to improve the QoE in WAN environments. We consider the benefits on the QoE as well as the costs on network layer.

The complex multi-hop structure of WMNs requires a careful network planning. In this paper, we investigate the usability of Genetic Algorithms (GAs) for such a planning approach. The simplicity of GAs allow us to examine a large number of network configurations in order to optimize the network throughput and to fairly distribute the resources. This is achieved with a max-min fair share throughput distribution and by evaluating node positions, routing configurations, and channel assignments. We adapt standard genetic operators and evaluate the influence of the operators on the performance. The results show that GAs are well-suited for planning WMNs.

IEEE 802.11s is an emerging IEEE 802.11 amendment, aiming at standardizing wireless mesh networking. As congestion is a major problem in wireless mesh networks, IEEE 802.11s addresses this problem by introducing the intra-mesh congestion control. In order to explore the potential of this mechanism, we describe two different IEEE 802.11s compliant congestion control mechanisms and discuss their respective benefits and limitations. Results from a simulative evaluation demonstrate that intra-mesh congestion control is suitable for avoiding the loss of packets which have already been forwarded over the air interface and, if appropriately implemented, increases the overall network throughput. The results do however also point out the limitations of the proposed IEEE 802.11s congestion notification format.

Building wireless sensor networks based on the IEEE 802.15.4 standard is an interesting option, as the standard enables low-power, low data rate wireless communication. Many authors analyzed and optimized the operational phase of such networks. In contrast, the initial phase, containing the 802.15.4 association procedure, has mostly been neglected. In this paper, we therefore propose four optimization possibilities for the association procedure of a nonbeacon-enabled sensor network. Our results show that significant performance improvements in terms of association probability, speed, and energy consumptions can be achieved.

Wireless Mesh Networks (WMNs) are a promising technology for providing broadband wireless access to the end user. They offer a higher degree of flexibility compared to traditional networks but on the expense of a more complex structure. Thus, planning and optimization of WMNs is a challenge. In this paper, we address this challenge using genetic algorithms. Genetic algorithms are able to evaluate and optimize large-scale WMNs in relatively small computation time. The results prove the effectiveness of the genetic operators to optimize the routing and channel assignment in WMNs.

Wireless Mesh Networks (WMNs) are gaining an increasingly important role in next generation last mile access. They offer more flexibility compared to traditional networks but on the expense of a complex structure. Thus, planning and optimization of WMNs is a challenge. In this paper we focus on routing and channel assignment in WMNs for throughput maximization using genetic algorithms. Genetic algorithms provide a good solution for large-scale WMNs in relatively small computation time. The results prove the effectiveness of the genetic operators and show the advantages of a genetic optimization. However, these operators have to be configured carefully to avoid local optima. We will show the influence of the selection principles as well as evaluation functions on the optimization.

Wireless mesh networks (WMNs) support a variety of modulation and coding schemes (MCSs) and hence enable adaptive modulation and coding. On the one hand, adaptive modulation and coding significantly increases the overall system capacity, as it allows to maximize the throughput on each link in dependence of the channel conditions. On the other hand, there is a trade-off between link data rate and spatial reuse, as high data rate links are less robust against interference. For maximizing the wireless mesh network performance, an intelligent link rate assignment strategy is thus required. By evaluating the maxmin fair WMN throughput under different link rate assignment strategies, we are able to show that using more robust MCSs improve the overall WMN throughput and point out directions towards an optimized MCS choice.

Wireless Mesh networks are multi-hop networks mostly based on IEEE 802.11 technology and are considered as a viable alternative for providing broadband wireless Internet access. As a consequence, they require support for Quality of Service or advanced mechanisms for selecting Internet gateways. One important required information is the one-way delay between different nodes. In this paper, we have developed, implemented, and evaluated an one-way delay estimation technique for wireless mesh networks which is based on estimating intra node queuing and inter node forwarding delay. An IP-header option field is used to accumulate the per hop delay estimate to provide an end-to-end estimate. We also outline problems with the implementation and compare results with real one-way delays obtained from a 14 node mesh testbed. We show how estimation accuracy depends on network load and provide insights into further improvements.

IEEE 802.15.4 proposes the advantage of a standardized low power low data rate communication stack and is thereforealso an option for deploying low power wireless sensor networks (WSNs). Most studies of 802.15.4 based WSNs concentrate on the operational phase and neglected the initial startup phase. Thisb ears however also potentials for energy savings, as the 802.15.4 association procedure has to be executed to make the network operational and is not ptimized for low power networks. In this study, we point out directions how to perform the association in a self organizing and energy saving way.

In this paper large scale multihop sensor networks are established as non-beacon enabled ZigBee mesh networks. The lifetime of the network is increased by putting nodes to sleep and to wakeup state autonomously. To enable a reliable system with sensor nodes sleeping in an asynchronous manner, we propose a cross-layer sleep scheduling solution coupled with ZigBee’s proposed AODV routing. It consists of two parts: a) Neighbor Aware Communication (NAC) and b) Adaptive Resynchronization (AR). NAC avoids sending packets to sleeping nodes while AR allows the sensor nodes to adapt their sleeping schedule to their neighbors’ duty cycles. ns-2-simulations show that the performance of such a cross-layer optimized system in terms of end-to-end delay and packet delivery ratio is comparable to the benchmark case of synchronized sleep schedules.

Quality of Experience (QoE) is a measure for the satisfaction of a user with a given service. Despite the popularity of the term, there is a lack of understanding of how to capture or quantify QoE. In this paper we therefore take a step forward in this direction using the example of thin client architectures, where the client is only used as a dumb terminal while the applications run on a central server. The satisfaction of a thin client user is thus heavily influenced by the quality of the network connection between the client and the server. We study this influence by varying different network parameters like packet loss, jitter, and delay in a controlled testbed environment. The service quality is assessed using objective measurements on application level (oQoE) and verified by means of a survey among test persons capturing subjective user satisfactions (sQoE).

The basic idea behind thin-client architectures is to run applications on a central server instead of installing them separately on each client. The Windows Remote Desktop Protocol (RDP) and the Citrix Presentation Server are two well known approaches to separate the location of where the user input is processed from the computer he is actually working on. While both alternatives solve the same problem, they rely on significantly different mechanisms to handle the exchange of user input and screen updates between client and server. In this paper we therefore compare the performance of both protocols under different aspects. In particular, we study the load caused on network layer as well as the satisfaction of the end user with the service quality achieved by the different terminal services. As this performance heavily depends on the current network conditions, we emulate realistic scenarios in a controlled testbed environment and measure the time required for typical office tasks on application layer. As a result, we quantify the Quality-of-Experience (QoE) perceived by the end-user, compare the overhead required by the different available protocols, and unveil their advantages and disadvantages. Our results can be used to decide which protocol to use in which scenario.

Models and proposals for capturing the energy consumption of sensor nodes are plentiful. The majority of those approaches roughly agree about the energy consumed in the states of the sensor node duty cycle, but the costs of radio operations are abstracted very differently. In our work, we establish a general framework whose modular structure allows to compare existing abstractions and to investigate which factors are crucial for the modeling of transmission costs. We analyze the influence of typical assumptions on the creation of energy efficient routing topologies. For this purpose the resulting routing trees are not only compared by topological characteristics, but also by estimating radio related energy consumptions, a metric which changes strongly with the MAC layer efficiency.

Large wireless sensor network deployments used for environ- mental monitoring or cargo tracking, require energy efficient mesh topologies. This implies duty cycling of sensor nodes to be coordinated with the routing protocol. Staying in the context of ZigBee, we simulate the combination of the sleep enabled non-beaconed mode of 802.15.4 and AODV routing and compare the duty cycling effects of synchronized and unsynchronized sleep scheduling. We consider two different link layer feedback schemes for AODV, denoted as regular and smooth AODV.